code: def forward(self, cond: Tensor) -> Tensor:
      for _ in range(self.num_stages):
          cond = self.interpolator(cond)
      if self.channel_mapper is not None:
          cond = self.channel_mapper(cond)
      return cond
  
file_path: carefree-learn/cflearn/models/cv/diffusion/cond_models/rescaler.py
imports: import torch.nn
  import torch.nn.functional
  from torch import Tensor
  from typing import Optional
  from functools import partial
  from .schema import ISpecializedConditionModel
  from .....modules.blocks import HijackConv2d
label_desc: Use image node_id 2 for calling the SpatialRescaler obj's underlying member method code with example usage: obj.forward(cond) and returns: cond